School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, PR China.
Department of Developmental and Behavioral Pediatrics, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, PR China.
Sci Total Environ. 2020 Aug 10;729:138871. doi: 10.1016/j.scitotenv.2020.138871. Epub 2020 Apr 23.
The reaction with hydroxyl radicals (•OH) is an important way to remove the most volatile organic compounds (VOCs) in atmospheric environment. Thus, the reaction rate constant (k) is important for assessing the persistence and exposure risk of VOCs, and is of great significance in evaluating the ecological risk of volatile organic chemicals. Fukui indices and bond order have a large effect on the degradation of VOCs, but so far, quantitative structure activity relationship (QSAR) models for VOCs degradation have rarely been considered these two factors. In this study, these two momentous factors will be considered along with other relevant quantitative parameters. A total of 180 substances are divided into training set (144 substances) and test set (36 substances), which are used to build and validate quantitative structure activity relationship (QSAR) models, respectively. Internal, external verification and y-randomization tests showed that the established model had excellent stability and reliability. The energy of the highest occupied molecular orbital (E), the possibility of being attacked by radicals (f (0)) and the breaking of chemical bonds (BO) are the main factors affecting VOCs removal. Finally, the scope of the application domain was determined and the robustness of the model was further verified.
与羟基自由基（•OH）的反应是去除大气环境中最易挥发有机化合物（VOCs）的重要途径。因此，反应速率常数（k）对于评估 VOCs 的持久性和暴露风险非常重要，对于评估挥发性有机化学品的生态风险也具有重要意义。福井指数和键序对 VOCs 的降解有很大影响，但到目前为止，VOCs 降解的定量构效关系（QSAR）模型很少考虑这两个因素。在这项研究中，将考虑这两个重要因素以及其他相关定量参数。总共 180 种物质被分为训练集（144 种物质）和测试集（36 种物质），分别用于构建和验证定量构效关系（QSAR）模型。内部、外部验证和 y-随机化测试表明，所建立的模型具有出色的稳定性和可靠性。最高占据分子轨道能量（E）、被自由基攻击的可能性（f（0））和化学键断裂（BO）是影响 VOCs 去除的主要因素。最后，确定了适用域范围，并进一步验证了模型的稳健性。
